Abstract
The wealth index based on household assets and amenities is been increasingly used to explain economic variations of health outcomes in the developing countries. While the variables used to compute the wealth index are easy to collect and time- and cost-effective, the wealth index tends to have an urban bias, uses arbitrary weighting, does not provide per capita measures and is a poor measure of inequality. We used micro data from two of the large-scale population-based surveys, the Longitudinal Ageing Study in India, 2017-18 and the India Human Development Survey, 2011-12 that covered over 42,000 households each and collected data on household consumption, assets and amenities in India. We examined the variations and inequality in health estimates by consumption per capita and asset-based measures in India. Descriptive statistics, logistic regression model, concentration index, and concentration curve were used in the analyses. We found a weak association between monthly per capita consumption expenditure (MPCE) and wealth index in both the surveys. Some of the health conditions such as hypertension, cataract, refractive error, and diabetes tended to be underestimated in the bottom 40% of the population when economic well-being was measured using the wealth index compared to consumption. Socio-economic inequality in health outcome, inpatient and outpatient health services were underestimated when measured using the wealth index than when measured using MPCE. We conclude that economic gradients of health by consumption and wealth index are inconsistent and that per capita consumption predicts health estimates better than the wealth index. It is recommended that public health research using population-based surveys that provide data on consumption and wealth index use per capita consumption to explain economic variations in health and health care utilization. We also suggest that the future rounds of the health surveys of National Sample Survey and the National Family and Health Surveys include an abridged version of the consumption schedule to predict better economic variations in health and health care utilization in India.